Effective Presenting with ‘Think, Feel, Do!’
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Effective research needs to result in outcomes, and changes that are beneficial to the organisation commissioning the research. The ability of the research to help bring about change depends on how it is communicated. In many cases, the only part of the research that has any impact or visibility is the presentation, i.e. the actual presentation and any report / ‘leave behind’/ or 'take-aways'. In this webinar, Ray Poynter, focuses on how to use the ‘Think, Feel, Do!’ approach to create effective communications, i.e. communications that result in actions.
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Effective Presenting with ‘Think, Feel, Do!’
- 1. Effective Presenting with ‘Think, Feel, Do!’ Ray Poynter Webinar, 7 October 2020
- 3. The difference between means and ends Means Engagement Storytelling Visualisation End Action
- 5. Do! • Launch the product • Choose option A • Address customer dissatisfaction with check-in • Do more research • Cancel the project • Keep doing exactly what you are doing …
- 6. Finding the Do! Business Question Business Context Your data and analysis Do!
- 7. Changing Behaviour is Hard From Behavioural Economics, we know changing behaviour is hard. The ‘facts’ do not often change behaviour.
- 8. Changing Behaviour Inform the rider (Think) Motivate the elephant (Feel) Shape the path (Do!)
- 12. The Think Business Question Business Context Your data and analysis Think ->Do!
- 13. The Do! Defined by the Think Do! Feel Think
- 14. The Do! Created by the Feel Do! Feel Think
- 15. Think, Feel, Do Think – The facts are still important, they are platform that everything else is built on. Feel – People rarely change their beliefs or behaviour because of the facts – change happens at the emotional level. Do – Every story should be aimed at creating an outcome, an action that the teller wants the recipient to do.
- 16. Example – USA Movie Popcorn Center for Science in the Public Interest (CSPI). In 1994 it revealed that Medium bag popcorn = 37 grams saturated fat. USDA (United States Department for Agriculture). Recommended maximum = 20 grams. 20 37 0 10 20 30 40 Grams Fat USDA Max Popcorn
- 17. Creating Emotion = 37 grams ++ 37 grams
- 18. Movie Popcorn Think, Feel, Do • Think, the ‘facts’: – Popcorn has saturated fat, saturated fat is not good, there are limits • Feel – 3 junk meals in one day is dumb/gross • Do – When you are about to buy popcorn, think about all that fat, feel a bit sick/scared, buy something else
- 19. Robust Simplification Movie Popcorn Data About double your daily fat allowance Visual Story A day’s worth of unhealthy food
- 20. Movie Popcorn What was left out? • Other things in the popcorn, e.g. salt & sugar • Large bag of popcorn • Other foods eaten in movie theatres • Other comparators, e.g. normal daily meal
- 21. Structure
- 22. Narrative Flow •A beginning, middle, and end •The flow should be linear •Use storytelling devices (e.g. humour, personal anecdotes, interaction etc) to enhance the flow
- 23. What are the key elements? 1. Link to the project objectives 2. ‘Need to know’ not ‘nice to know’ 3. Supported by patterns or themes in the data • Not just a single data point 4. Clear findings • Try to ensure you are talking about large groups of people – ideally majorities For example: • If men are slightly more interested • If young people are slightly more interested • If people in London are slightly more interested • Check Young, Men in London – that may be the key message
- 24. Do Not (Normally) use the Questionnaire Sequence • Q1 by Age and Sex • Q1 by Region • Q2 by Age and Sex • Q2 by Region • :: • :: • Q1 by Age and Sex • Q2 by Age and Sex • :: • :: • Q1 by Region • Q2 by Region • :: • ::
- 25. Do Not (Normally) use the Questionnaire Sequence 0 5000 10000 15000 20000 25000 0 100 200 300 400 500 600 700 Brazil China France Germany India Italy Japan Russia South Africa Sweden UK USA World CasesPerMillion DeathsPerMillion Deaths and Cases Per Million of Population (until 27 September 2020) Deaths / 1Million Case / 1MillionSorted by alphabet https://www.worldometers.info/coronavirus/ - downloaded 27 September 2020
- 26. Sort the data by something meaningful 0 5000 10000 15000 20000 25000 0 100 200 300 400 500 600 700 Brazil USA UK Italy Sweden France South Africa Russia World Germany India Japan China CasesPerMillion DeathsPerMillion Deaths and Cases Per Million of Population (until 27 September 2020) Deaths / 1Million Case / 1MillionSorted by declining number of deaths per million https://www.worldometers.info/coronavirus/ downloaded 27 September 2020
- 27. Typical Structure The Lead / Elevator Pitch Executive Summary Three themes T1, T2, T3 Do Theme 1 Theme 2 Theme 3 Evidence 1a, 1b, 1c Evidence 2a, 2b, 2c Evidence 3a, 3b, 3c Close with the Do! Appendix (Treasure Chest) HT, Mike Sherman
- 28. Three Pieces of Evidence • Focus on contrast, not repetition – Different people learn in different ways • For example: – Quantitative evidence – Qualitative evidence – Video, open-ends, analytics
- 29. The Lead Nora Ephron When Harry Met Sally Sleepless in Seattle 1st Day in Journalism School 5 Ws (Who, What, When, Where & Why?) Asked to write the Lead for the school newspaper “The entire school faculty will travel to Sacramento next Thursday for a colloquium in new teaching methods. Among the speakers will be anthropologist Margaret Mead, college president Dr. Robert Maynard Hutchins, and California Governor Edmund Brown.” All the students wrote about the 5Ws – good, but not right. The Lead? No school next Thursday!
- 30. Truth Not Precision MOVE! TruthPrecision Precision vs Truth in the real world
- 31. The Appendix
- 32. The Appendix • Explain it is a Treasure Chest – Not a garbage dump • Make the information is easier to find – A mix of tables, notes, and visuals • It does not have to be one document – It does not have to be in one place • It needs to be one concept – A single lookup system – accessing all the parts
- 33. 33 Storyboarding
- 34. Feelings
- 35. The Weak Link Between Finding the Story and Telling the Story In finding the story we have multiple data sources We have many analytical tools to find the story in the data • For example, you might use predictive analytics to find the story But, the best way to tell the story does not have to rest on the ‘best’ data • You might use an image or consumer video to tell the story
- 36. Research shows we make too many mistakes You learned this from the data, but the image conveys the message.
- 37. Use Analogies • Explaining a joke is like dissecting a frog. You understand it better but the frog dies in the process. • Pitching the film: Alien ‘like Jaws in space’ • ‘AI and big data is like high school sex, everybody is talking about it, but nobody is actually doing it’
- 38. Take one thing away from the ecosystem and the whole system collapses.
- 39. Memes
- 40. Tip – Collect Examples
- 42. The Story? • It is all about the Do! • Use Think to find the Do! • Use Feel to cause the Do! • Structure your presentation to deliver the Do! – The Lead – The Story – The Recommendation
- 43. Q & A